Forecasting Under Five Mortality Rate for Solomon Islands Using a Machine Learning Approach

Dr. Smartson. P. NYONIZICHIRe Project, University of Zimbabwe, Harare, ZimbabweThabani NYONIIndependent Researcher & Health Economist, Harare, Zimbabwe

Vol 6 No 7 (2022): Volume 6, Issue 7, July 2022 | Pages: 466-469

International Research Journal of Innovations in Engineering and Technology

OPEN ACCESS | Research Article | Published Date: 06-09-2022

doi Logo doi.org/10.47001/IRJIET/2022.607103

Abstract

This study uses annual time series data on under five mortality rate (U5MR) for Solomon Islands from 1960 to 2020 to predict future trends of U5MR over the period 2021 to 2030. Residuals and forecast evaluation criteria indicate that the applied ANN (12, 12, 1) model is stable in forecasting U5MR. ANN model projections indicate that annual U5MR will hover around 20 deaths per 1000 live births throughout the out of sample period. Therefore, we encourage the government of Solomon Islands to address all the major challenges that may hinder the success of the maternal and child health program. 

Keywords

ANN, Forecasting, U5MR


Citation of this Article

Dr. Smartson. P. NYONI, Thabani NYONI, “Forecasting Under Five Mortality Rate for Solomon Islands Using a Machine Learning Approach” Published in International Research Journal of Innovations in Engineering and Technology - IRJIET, Volume 6, Issue 7, pp 466-469, July 2022. Article DOI https://doi.org/10.47001/IRJIET/2022.607103

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